| Budget Amount *help |
¥6,370,000 (Direct Cost: ¥4,900,000、Indirect Cost: ¥1,470,000)
Fiscal Year 2019: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2018: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2017: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Outline of Final Research Achievements |
Language is absolutely essential for a robot to be implemented into our daily life that lies on the highly sophisticated intelligence based on symbols and language. In this research, we have presented a stochastic mathematical model with multiple hidden layers to represent the association between human motions and their descriptive language. The motions and language set to the input and output layer, respectively. The input layer are connected to the output layer via multiple hidden layers, and the connection is specified the probabilistic parameters, such as probability of hidden state being generated from an input. We have derived an algorithm to optimize these parameters. It implies than the association between the motion and language can be extracted as the distribution of hidden variables in their space. This model makes it possible to convert motion data into their descriptive sentence.
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